PROJECT

Setup R notebook Environment

knitr::opts_chunk$set(echo = TRUE)
Sys.setlocale("LC_CTYPE", "en_US.UTF-8")

[1] ""

1 Package load for Project

packages = c("sp","sf","tidyverse","tmap","rjson", "rgdal", "geojsonio", "GISTools",'spatialEco', "raster","dplyr","spdep") 
for (p in packages){
  if(!require(p, character.only = T)){
    install.packages(p) 
  } 
  library(p,character.only = T) 
}

Loading required package: sf
Linking to GEOS 3.6.1, GDAL 2.2.3, PROJ 4.9.3
Loading required package: tidyverse
-- Attaching packages --------------------------------------- tidyverse 1.2.1 --
v ggplot2 3.1.0     v purrr   0.2.5
v tibble  1.4.2     v dplyr   0.7.8
v tidyr   0.8.2     v stringr 1.3.1
v readr   1.3.1     v forcats 0.3.0
-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()
Loading required package: tmap
Loading required package: rjson
Loading required package: rgdal
rgdal: version: 1.3-6, (SVN revision 773)
 Geospatial Data Abstraction Library extensions to R successfully loaded
 Loaded GDAL runtime: GDAL 2.2.3, released 2017/11/20
 Path to GDAL shared files: C:/Users/terence.tan.2015/Documents/R/win-library/3.5/rgdal/gdal
 GDAL binary built with GEOS: TRUE 
 Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493]
 Path to PROJ.4 shared files: C:/Users/terence.tan.2015/Documents/R/win-library/3.5/rgdal/proj
 Linking to sp version: 1.3-1 
Loading required package: geojsonio

Attaching package: <U+393C><U+3E31>geojsonio<U+393C><U+3E32>

The following object is masked from <U+393C><U+3E31>package:base<U+393C><U+3E32>:

    pretty

Loading required package: GISTools
Loading required package: maptools
Checking rgeos availability: TRUE
Loading required package: RColorBrewer
Loading required package: MASS

Attaching package: <U+393C><U+3E31>MASS<U+393C><U+3E32>

The following object is masked from <U+393C><U+3E31>package:dplyr<U+393C><U+3E32>:

    select

Loading required package: rgeos
rgeos version: 0.4-2, (SVN revision 581)
 GEOS runtime version: 3.6.1-CAPI-1.10.1 
 Linking to sp version: 1.3-1 
 Polygon checking: TRUE 

Loading required package: spatialEco
Loading required package: raster

Attaching package: <U+393C><U+3E31>raster<U+393C><U+3E32>

The following objects are masked from <U+393C><U+3E31>package:MASS<U+393C><U+3E32>:

    area, select

The following object is masked from <U+393C><U+3E31>package:dplyr<U+393C><U+3E32>:

    select

The following object is masked from <U+393C><U+3E31>package:tidyr<U+393C><U+3E32>:

    extract

Loading required package: spdep
Loading required package: Matrix

Attaching package: <U+393C><U+3E31>Matrix<U+393C><U+3E32>

The following object is masked from <U+393C><U+3E31>package:tidyr<U+393C><U+3E32>:

    expand

Loading required package: spData
To access larger datasets in this package, install the spDataLarge package with:
`install.packages('spDataLarge', repos='https://nowosad.github.io/drat/', type='source')`

Attaching package: <U+393C><U+3E31>spData<U+393C><U+3E32>

The following object is masked _by_ <U+393C><U+3E31>.GlobalEnv<U+393C><U+3E32>:

    x

The following object is masked from <U+393C><U+3E31>package:spatialEco<U+393C><U+3E32>:

    elev

2 Importing Taiwan GDAM Subzone

Shapefile Object with Spatial data Import data for past 12 years

Requires translation of chinese character independetly (https://stat.ethz.ch/pipermail/r-sig-geo/2009-March/005323.html)

Taiwan follows EPSG 3826 (http://spatialreference.org/ref/epsg/twd97-tm2-zone-121/)

taiwan_ts_map_sp <- readOGR(dsn = "data/TAIWAN_TOWNSHIP", layer = "TOWN_MOI_1071226", stringsAsFactors=TRUE)

OGR data source with driver: ESRI Shapefile 
Source: "C:\Users\terence.tan.2015\Desktop\dangy\data\TAIWAN_TOWNSHIP", layer: "TOWN_MOI_1071226"
with 368 features
It has 7 fields

df_dengue <- jsonlite::fromJSON("data/dengue_case.json") %>% 
  filter(as.Date(Onset_day) >= "2016-01-01" & as.Date(Onset_day)< "2017-01-01")
# Check for NA values for coordinates
 sum(is.na(df_dengue$Minimum_statistical_area_center_point_X))

[1] 0

 sum(is.na(df_dengue$Minimum_statistical_area_center_point_Y))

[1] 0

 df_dengue<- df_dengue[!is.na(df_dengue$Minimum_statistical_area_center_point_X),]
 df_dengue<- df_dengue[!(df_dengue$Minimum_statistical_area_center_point_X == 'None'),]
 
 # Type conversion
 df_dengue[, c(10,11,19,23,24)] <- sapply(df_dengue[, c(10,11,19,23,24)], as.numeric)
 
  # Transform into SF object
 sf_dengue <- st_as_sf(df_dengue, 
                       coords = c("Minimum_statistical_area_center_point_X",
                                  "Minimum_statistical_area_center_point_Y"),
                        crs = "+init=epsg:3826 +proj=longlat +ellps=WGS84 +no_defs",na.fail=FALSE)
sf_dengue <- na.omit(sf_dengue)
sf_dengue <- as(sf_dengue, 'Spatial')

Map name dict to map

#plot(taiwan_ts_map_sp, border="lightgrey")
#plot(transaction.boundary.poly, col="red",add=TRUE)
tmap_mode("plot")

tmap mode set to plotting

map <- tm_shape(taiwan_ts_map_sp)+
      tm_polygons('TOWNENG')+
       tm_borders(col = "grey40",alpha=0.5)+
  tm_view(alpha = 1)+
  tm_layout(basemaps = c('OpenStreetMap'))+
  tm_shape(sf_dengue)+
  tm_bubbles(col ="red",size = 0.1)

As of version 2.0, basemaps and basemaps.alpha have to be called from tm_view

#map 

#tmap_mode("view")
#map 

3 FEATURE 5 & 6

projection(taiwan_ts_map_sp) <- sf_dengue@proj4string
taiwan_ts_map_sp@data$poly.ids <- 1:nrow(taiwan_ts_map_sp)
#join poly and points
pts.poly <- point.in.poly(sf_dengue, taiwan_ts_map_sp)

although coordinates are longitude/latitude, st_intersects assumes that they are planar

#assign unique id per poly, full info

#descendng order of town with most
selected_aggregated_temp <-pts.poly@data %>% 
  dplyr::select(poly.ids, TOWNNAME, TOWNENG, Onset_day, Case_study_date, Notification_day) %>% 
  mutate(MONTH = months(as.Date(pts.poly@data$Onset_day))) %>%
  group_by(poly.ids,TOWNNAME, TOWNENG,MONTH) %>% 
  summarise(total_cases = n())
total_case_district <- selected_aggregated_temp %>%
   group_by(poly.ids) %>% 
    summarise(total_cases = n())
total_case_district <- merge(taiwan_ts_map_sp, total_case_district, by=c("poly.ids")) 
total_case_district@data <- total_case_district@data %>% 
  mutate(total_cases = ifelse(is.na(total_cases),0,total_cases))
tmap_mode("view")

tmap mode set to interactive viewing

tm_shape(total_case_district) +
  tm_fill(col="total_cases",id="TOWNENG",style="jenks")

4 Spatial Autocorrelation

taiwan_q <- poly2nb(taiwan_ts_map_sp, queen=TRUE)
plot(taiwan_ts_map_sp, border="lightgrey") 

plot(taiwan_q, coordinates(taiwan_q), pch = 19, cex = 0.6, add = TRUE, col= "red") 

Error in (function (classes, fdef, mtable)  : 
  unable to find an inherited method for function ‘coordinates’ for signature ‘"nb"’